Image Processing Mechanism for Augmented Reality based Autonomous Navigation

This paper proposes a novel image processing mechanism for augmented reality based autonomous navigation system. Autonomous vehicles navigate independently without any sort of human assistance. In order to navigate from one location to another, these systems require assistance in the form of markers i.e., bookmarks or reference points which are pre-determined and already stored in a database. This approach makes it difficult for the vehicle to navigate in an unknown and uncertain environment. Therefore, the proposed system will navigate on its own without any pre-trained dataset. Three types of markers are detected and stored in the intelligent repository by eliminating step by step triviality. Optical flow and image processing techniques have been proposed to detect markers from the real time video frames. This approach is divided into three parts: (i) Marker detection and categorization; (ii) Marker Identification and (iii) Obstacle detection. Obstacles are also detected during run time without any training of dataset. This will result in minimizing the gap between human and machine thinking skills.